Top Software Engineer Jobs

Build and ship native iOS features in Swift for a finance super app. Design clean user flows for insurance, payments, claims and financial services, integrate backend APIs, improve performance and reliability, use analytics to iterate, and add AI-assisted on-device experiences where beneficial.

You will build agentic AI products across web, backend, and iOS, owning features end-to-end and mentoring junior teammates.

Design, develop, test, deploy, and maintain backend services and data pipelines. Ensure technical and product excellence, performance, and engineering best practices. Collaborate across global teams, drive projects, and contribute to large-scale system design and distributed computing challenges.

Design, develop, and maintain enterprise full‑stack applications; implement AI/ML pipelines and RAG systems; ensure DOE compliance and hardened security; collaborate with infrastructure and security teams; support CI/CD, containerization, and production incident response.

Administer, govern, and scale Microsoft Power Platform and AI automation across enterprise environments. Design and develop Power Apps, Power Automate flows, Copilot Studio agents, and integrations (Microsoft 365, Dataverse, APIs). Enable CoE adoption through training, governance, monitoring, ALM, and citizen-developer support while ensuring compliance, validation, and operational excellence in regulated settings.

Lead design, development, testing, and App Store submission of production-scale iOS features in Swift. Collaborate cross-functionally, enforce code quality via reviews and refactoring, maintain technical documentation, and adopt AI-assisted tooling to improve productivity across large, user-facing modules.

Develop and maintain AI-driven features, design scalable data structures and pipelines, and enhance platform capabilities while collaborating with teams.

As an AI-native Software Engineer, you will optimize developer experience and create tools for AI coding to enhance efficiency at Cartesia.

As a Forward Deployed Engineer, you will develop AI agents and automation workflows, collaborate with teams, and ensure secure, reliable solutions integrating with various systems.

The Engineering Manager will lead a cross-continent team to enhance engineering productivity using AI tools, collaborate across departments, and deliver innovative product experiences.

Own product areas end-to-end: discover, prototype, ship, and iterate. Build secure, well-tested, observable full‑stack systems; partner with product, design, data, and clinical teams; use data and experimentation to validate impact; improve AI‑native development practices and engineering systems while balancing speed, safety, and reliability in a regulated healthcare context.

The AI Data Engineer will design and implement data pipelines, build AI-optimized data infrastructure, ensure data quality, and collaborate with teams to support AI applications.

Design, develop, test, operate and maintain full‑stack web applications with emphasis on frontend and backend integration. Write production-ready code, follow DevOps/CI-CD and security/compliance standards, perform code reviews, troubleshoot failures, and contribute to scalable, reliable architectures and reusable component libraries.

Develop and maintain backend services for an MDM platform using Java, Spring Boot, and REST APIs. Build data ingestion, transformation, and integration pipelines, apply observability and testing best practices, optimize performance, and use AI-assisted tools to accelerate development. Collaborate in Agile teams across frontend, QA, product, and platform.

The role involves researching and developing GPU-accelerated AI workloads, optimizing algorithms, and collaborating with technical experts to improve hardware performance.

Lead a team to optimize algorithms for Deep Learning and Machine Learning, define technical initiatives, and collaborate with various teams for hardware and software innovation.

As a Full-Stack Engineer at Labelbox, you will develop and maintain AI tools, focusing on data training systems, intermediate user interfaces, scalable architectures, and work in a collaborative, fast-paced environment.

Senior full‑stack engineer responsible for building production-quality Salesforce platform capabilities, integrations (MuleSoft, REST/SOAP), AI-enabled tooling (Claude plugins, MCP servers), CI/CD, and reusable libraries. Mentor engineers, run architecture/code reviews, and collaborate cross-functionally to deliver scalable, secure cloud-native solutions using Python, LWC, Apex, and AWS.

Design, develop, and operationalize full-stack, cloud-native applications for transaction monitoring and data controls. Build responsive UIs and Java-based microservices, integrate event-driven pipelines (Kafka, Spark), deploy on GCP (App Engine, GKE, Cloud Run), and implement LLM/Agentic AI and RAG automation while ensuring performance, resiliency, observability, and security.

As a Principal Software Engineer, you will lead AI networking system transformations, manage complex customer engagements, and influence NVIDIA's networking technologies.

Lead a small team to accelerate software engineering productivity across a global organization by improving developer workflows, tooling, testing, code review, documentation, and AI-enabled development practices. Identify bottlenecks, drive scalable engineering systems and reusable patterns, and measure productivity gains across polyglot teams and legacy platforms.

Lead the technical architecture and implementation for LangSmith, collaborating with teams, mentoring juniors, and ensuring code quality.

The Full Stack Engineer will develop and implement features for the LangSmith platform, collaborate with teams, ensure high coding standards, and engage with enterprise customers.

The Senior Flutter Engineer will own the mobile platform, focusing on audio recording, offline capabilities, cross-platform stability, and CI/CD pipeline maintenance, while mentoring junior engineers.

The AI Product Engineer will build AI-driven software features, enhance performance, and develop intelligent UIs, working across product and infrastructure layers.